To avoid overffiting issues when updating all model parameters with limited adaptation data, we split model parameters into style specific parameters and shared parameters. In what follows, we term the proposed model as Meta-Voice for clarity.
As illustrated in Fig. REF , we transfer the shared parameters from a multi-speaker and multi-prosody base TTS model pre-trained with a large-scale corpus and conduct meta-training on the style specific parameters to a state which is highly sensitive for fast adaptation with only few samples from a new speaker.
For the purpose of style transfer, we adopt domain adversarial training mechanism [1]} and orthogonal constraint [2]} to disentangle speaker and prosody representations.
The contributions of this work are summarized as follows:
